Yazar "Elgammal, Khaled Walid" seçeneğine göre listele

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    Identification of the number of wireless channel taps using deep neural networks
    (Institute of Electrical and Electronics Engineers Inc., 2021) Jaradat, Ahmad M.; Elgammal, Khaled Walid; Özdemir, Mehmet Kemal; Arslan, Hüseyin
    In wireless communication systems, identifying the number of channel taps offers an enhanced estimation of the channel impulse response (CIR). In this work, efficient identification of the number of wireless channel taps has been achieved via deep neural networks (DNNs), where we modified an existing DNN and analyzed its convergence performance using only the transmitted and received signals of a wireless system. The displayed results demonstrate that the adopted DNN accomplishes superior performance in identifying the number of channel taps, as compared to an existing algorithm called Spectrum Weighted Identification of Signal Sources (SWISS).
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    Low-complexity deep learning-based beamforming in MISO systems
    (Institute of Electrical and Electronics Engineers Inc., 2021) Thet, Nann Win Moe; Elgammal, Khaled Walid; Ateş, Hasan Fehmi; Özdemir, Mehmet Kemal
    This study proposes a low-complexity deep learning-based beamforming neural network (BFNN) for massive multiple-input single-output (MISO) systems. We adopt an unsupervised learning-based convolutional neural network (CNN) model. The network is trained to obtain an analog phase shifters (PSs)-based beamforming vector of a given user by maximizing the system spectral efficiency (SE) while maintaining the transmitted power constraint. The channel state information (CSI) for millimeter wave (mmWave) channel and signal-to-noise-ratio (SNR) are used as inputs to the network. We also proposed a novel input feeding arrangement to the network and assessed its performance by using different input data representations. Simulation results show that the CNN-BFNN has the lowest complexity compared to a fully connected neural network (FCNN) and the existing conventional algorithms. Furthermore, the CNN model with fast Fourier transform (FFT) input provides the highest SE performance among all other input data representations.
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    Signal of opportunity based TDOA positioning using analog TV signals
    (IEEE Computer Society, 2023) Elgammal, Khaled Walid; Turan, Berke Can; Bedir, Oğuz; Çelebi, Hasari; Özdemir, Mehmet Kemal
    The ability to self-localize is an essential requirement for many systems. Mostly, this is accomplished by using a Global Positioning System (GPS) receiver. However, in some situations, the GPS receiver is disabled by external factors. Signal-Of-Opportunity (SoOP)-based localization is a popular substitute solution. TV broadcasting can be utilized for SoOP-based self-localization. In this paper, we collect measurements of Phase Alternating Modulation (PAL) analog TV broadcasting to aid the localization model. Specifically, we use these measurements to achieve a Time-Difference Of Arrival (TDOA) localization of one receiver with the knowledge of the coordinates of four transmitters and a reference receiver. The histogram of the localization error shows that the average error hits the theoretical limit of the employed bandwidth or the limit set by the time resolution of the samples.
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    Software implementation of key transceiver algorithms for an in-band full-duplex DVB-S2-based satellite communication system
    (İstanbul Medipol Üniversitesi Fen Bilimleri Enstitüsü, 2021) Elgammal, Khaled Walid; Özdemir, Mehmet Kemal
    Nowadays, the demand for satellite bandwidth is boosted driven by the introduction of new areas of applications such as 5G-satellite integration and the internet of things. In-Band Full-Duplex communications, where a satellite relay down-converts both uplink messages onto one downlink spectrum carrier, offers doubling the downlink spectrum capacity and reducing the operation expenditure significantly. In this thesis, we develop and test a self-interference scheme for satellite communication scenario in which the satellite acts as a bent-pipe relay. In this scenario, both messages from both transceivers are set on the same downlink bandwidth at the satellite. The proposed system operates in the presence of time & frequency offsets and noise. The system removes the self-interference and compensates for frequency and residual phase offsets. Matlab simulation shows that the proposed scheme is able to achieve a biterror-rate value comparable to that of a frequency-offset-free conventional halfduplex system in the cost of additional signal-to-noise ratio. Moreover, the rootmean-square error in estimating the echo of the transmitted signal is minor. The proposed "digital video broadcasting - satellite - second generation"-based system can be used for a wide set of applications such as mobile backhaul, IP trunking, personal communications, and Maritime communication.
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    Theoretical limits of soop tdoa localization of unmanned systems with imperfect synchronization
    (2023) Elgammal, Khaled Walid; Turan, Berke Can; Bedir, Oğuz; Çelebi, Hasari; Qaraqe, Marwa K.; Özdemir, Mehmet Kemal
    Self-localization is of crucial importance to Unmanned Aerial Vehicle (UAV) industry. Localization systems such as the Global Positioning System (GPS) are prone to jamming and spoofing. Localization using the Signal-Of-Opportunity (SoOP) gained much attention recently as an alternative to typical localization systems. We consider a general scenario where a receiver deployed on a mobile UAV finds its location based on Time Difference Of Arrival (TDOA) measurements with a number of unsynchronized reference Base Station (BS) receivers using signals from unsynchronized transmitters. The UAV has relative time offsets and clock skews with the BSs. We derive the Cramer-Rao Lower Bound (CRLB) of the UAV location and relative skews. Then, we plot them for Phase Alternating Line (PAL) analog TV transmission as SoOP.